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| import os | |
| import threading | |
| import time | |
| import subprocess | |
| OLLAMA = os.path.expanduser("~/ollama") | |
| if not os.path.exists(OLLAMA): | |
| subprocess.run("curl -L https://ollama.com/download/ollama-linux-amd64 -o ~/ollama", shell=True) | |
| os.chmod(OLLAMA, 0o755) | |
| def ollama_service_thread(): | |
| subprocess.run("~/ollama serve", shell=True) | |
| OLLAMA_SERVICE_THREAD = threading.Thread(target=ollama_service_thread) | |
| OLLAMA_SERVICE_THREAD.start() | |
| print("Giving ollama serve a moment") | |
| time.sleep(10) | |
| subprocess.run("~/ollama pull gemma2", shell=True) | |
| import copy | |
| import gradio as gr | |
| from ollama import Client | |
| client = Client(host='http://localhost:11434', timeout=60) | |
| HF_TOKEN = os.environ.get("HF_TOKEN", None) | |
| MODEL_ID = os.environ.get("MODEL_ID", "google/gemma-2-9b-it") | |
| MODEL_NAME = MODEL_ID.split("/")[-1] | |
| TITLE = "<h1><center>Chatbox</center></h1>" | |
| DESCRIPTION = f""" | |
| <h3>MODEL: <a href="https://hf.co/{MODEL_ID}">{MODEL_NAME}</a></h3> | |
| <center> | |
| <p>Gemma is the large language model built by Google. | |
| <br> | |
| Feel free to test without log. | |
| </p> | |
| </center> | |
| """ | |
| CSS = """ | |
| .duplicate-button { | |
| margin: auto !important; | |
| color: white !important; | |
| background: black !important; | |
| border-radius: 100vh !important; | |
| } | |
| h3 { | |
| text-align: center; | |
| } | |
| """ | |
| def stream_chat(message: str, history: list, temperature: float, max_new_tokens: int, top_p: float, top_k: int, penalty: float): | |
| print(f'message is - {message}') | |
| print(f'history is - {history}') | |
| conversation = [] | |
| for prompt, answer in history: | |
| conversation.extend([ | |
| {"role": "user", "content": prompt}, | |
| {"role": "assistant", "content": answer}, | |
| ]) | |
| conversation.append({"role": "user", "content": message}) | |
| print(f"Conversation is -\n{conversation}") | |
| response = client.chat( | |
| model="gemma2", | |
| messages=conversation, | |
| stream=True, | |
| options={ | |
| 'num_predict': max_new_tokens, | |
| 'temperature': temperature, | |
| 'top_p': top_p, | |
| 'top_k': top_k, | |
| 'repeat_penalty': penalty, | |
| }, | |
| ) | |
| buffer = "" | |
| for chunk in response: | |
| buffer += chunk["message"]["content"] | |
| yield buffer | |
| chatbot = gr.Chatbot(height=600) | |
| with gr.Blocks(css=CSS, theme="soft") as demo: | |
| gr.HTML(TITLE) | |
| gr.HTML(DESCRIPTION) | |
| gr.DuplicateButton(value="Duplicate Space for private use", elem_classes="duplicate-button") | |
| gr.ChatInterface( | |
| fn=stream_chat, | |
| chatbot=chatbot, | |
| fill_height=True, | |
| additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False), | |
| additional_inputs=[ | |
| gr.Slider( | |
| minimum=0, | |
| maximum=1, | |
| step=0.1, | |
| value=0.8, | |
| label="Temperature", | |
| render=False, | |
| ), | |
| gr.Slider( | |
| minimum=128, | |
| maximum=2048, | |
| step=1, | |
| value=1024, | |
| label="Max New Tokens", | |
| render=False, | |
| ), | |
| gr.Slider( | |
| minimum=0.0, | |
| maximum=1.0, | |
| step=0.1, | |
| value=0.8, | |
| label="top_p", | |
| render=False, | |
| ), | |
| gr.Slider( | |
| minimum=1, | |
| maximum=20, | |
| step=1, | |
| value=20, | |
| label="top_k", | |
| render=False, | |
| ), | |
| gr.Slider( | |
| minimum=0.0, | |
| maximum=2.0, | |
| step=0.1, | |
| value=1.0, | |
| label="Repetition penalty", | |
| render=False, | |
| ), | |
| ], | |
| examples=[ | |
| ["Help me study vocabulary: write a sentence for me to fill in the blank, and I'll try to pick the correct option."], | |
| ["What are 5 creative things I could do with my kids' art? I don't want to throw them away, but it's also so much clutter."], | |
| ["Tell me a random fun fact about the Roman Empire."], | |
| ["Show me a code snippet of a website's sticky header in CSS and JavaScript."], | |
| ], | |
| cache_examples=False, | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |